"A Geographical study of Tourism Potential with reference to Ware Beach in

Ratnagiri District (Maharashtra)”.

Sanjay B. Navale1*, Prof. (Dr.) Rajendra S. Suryawanshi

The e-mail address and telephone number(s) of the corresponding author

Sanjay B. Navale

Department of Geography,

S.N. Arts, D.J.M. Commerce and B.N.S. Science College, Sangamner, Dist.Ahmednagar,

Maharashtra (India). 422605.

* Corresponding author

Co-author:

Prof. (Dr.) Rajendra S. Suryawanshi,

Professor, Department of Geography, MES Abasaheb Garware College, Pune Maharashtra,

(India).

Abstract: This research was done for the Ware Beach in Ratnagiri district of Maharashtra. The

main objective of the research is to assess the tourism potential and its scenic beauty

of coastal sites. Arc GIS (10.3), Global Mapper (2013), Microsoft excel, Filed survey, Filed

observation and AHP method has been adopted for this research. In a real sense, this research is

based on theoretical and applied studies that have analyzed the potential of coastal tourism and its

natural beauty from a scientific point of view. In this research, the researcher adopted the

appropriate research method based on various research scientific literature materials. Using the

AHP techniques, calculated the beach , scenic value and the value of scientific investigation, the

weight of the each criteria and sub-parameter pairwise comparison matrixes was indicated by the

matrix method. In addition, the AHP technique is useful for studying the potential of coastal

tourism and the beauty of coastal tourism, and is also useful in tourism planning, development and

management in the study area.

Keywords: Tourism potential, Analytical Hierarchy Processes, Pairwise comparison Matrix

1. Introduction:

The tourism industry is known as the fastest growing industry in the world (Kisi 2019;

Priskin 2001). This industry has an impact on the economy of every country along with the

international economy. According to the data from 2006 to 2019, the revenue from the tourism

industry in the GDP of the global economy is about 9,258 billion US dollars (WTO, 2013). It is

imperative to develop tourism from the perspective of the country which has the most natural

potential for natural beauty and tourism development. This is because tourism provides a lot of

employment and increases economic productivity. Moreover, the large number of jobs available

to the locals helps to improve their economic situation (Samanta et al. 2018). The beach,

scenic value and beach scientific value were considered for study the natural beauty and

development potential of coastal tourism in the present research. The coastal slope, area size,

adjacent land uses, beach morphology landscape features, sand color, sea, lake flows, beach,

sunrise and sunset view, beach water clarity all these physical parameters were used for the

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geographical studies of scenic beauty and coastal tourism potential (Navale and Suryawanshi

2019).

Li Lin and Pussella 2017; Mani Murali et al. 2013; Francesca et al. 2018; Pralong and

Reynard 2005; Suryawanshi and Ranyewale 2018; Cetin and Sevik 2016; all above researcher

have been using using above tourist assessment values viz beach, scenic value (BSV) and beach

scientific investigation value (BSIV).Professor Thomas L. saaty (1970) was used AHP techniques

for solving complex problems related to group decision making based on Mathematics. The

method has been used around the world to solve a variety of environmental problems, therefore

researcher have chosen this method for research

2. Study area:

The Western Ghats in the “Sahyadri” Range are known as the “Konkan region”. Ratnagiri district

in this geographical region is rich in terms of natural resources. Moreover, the region has a good

coastline, which can be used for tourism development. That is why this part has been selected for

research. The geographical extent of this research is from 170 5’0'’s north of 170 6' 30’’ north

latitude and 730 16' 30’'east longitude (Figure 1). The natural beauty of this beach is great with

the Arabian Sea to the west, Ganpatipule Beach to the north and Aare beach nearby. Due to the

high geographical area on the east side of the coast, the beauty of this coastline is very good about

that place. The beautiful beach with white golden sand adds to the beauty of the beach and the

natural view of sunrise and sunset is very attractive for the tourists as the geographical location of

this beach is very good. As the region is coastal, the temperature is humid throughout the year.

Normally the temperature in this area is up to 30 degree Celsius in summer season. It is

characterized by more than 4000 mm of rainfall during the monsoon season. Majorly monsoon

season, skies are heavily clouded and wind velocities are very strong towards a southwesterly

direction up to western ghat (Figure1).

3. Research Method:

In order to identification the suitable tourism potential for ware beach, mainly physical parameters

like coastal slope, seas-lakes-streams, size of the area, beach Sand colour, beach water clarity,

adjacent land use, landscape features, beach morphology, beach sunrise and sunset view have

been assessed on the basis of field survey and literature review using GIS-based approach. The

AHP is one of the tools which are helping to solve complex decision making problems (Saaty,

1977). Therefore, the technique has been used for geographical study of coastal tourism potential

in this study in the following steps as below: (1) The source of the data (2) selection of criteria, (3)

score determination of criteria and sub-parameter, (4) weight calculation to criteria using a

pairwise comparison matrix (PCM), (5) weighted overlay analysis, and (6) tourism potential map

(Figure 2).

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Figure 1. Study area: Ware beach

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3.1 Source of the data:

The primary and secondary source data have been collected from field survey,

ASTER, topographic maps, Google image, Census of Ratnagiri district (2001,2011), and

Maharashtra Maritime board. The field work was carried out to collect the data about tourism

potential with the help of global positioning system (GPS) and identification of the study area and

surrounding physical feature's location (Table 1 and 2). GIS software was used for the preparation

of study area and tourism potential map.

Table1. Study area criteria, sub-parameter and sources

Criteria Sub-Parameter Sources

Beach Scenic

Value

(BSV)

Beach morphology Field survey, GPS data collection

Maharashtra Maritime Board

https://mahammb.maharashtra.gov.in

Google Image, Census of Ratnagiri district

(2001, 2011).

Landscape Features

Beach Sand colour

Beach Sunrise and sunset

view

Beach water clarity

Beach Scientific

investigatevalue

(BSIV)

Size of the area SOI (Survey of India )Toposheet 1:50000

Maharashtra Maritime Board

https://mahammb.maharashtra.gov.in

ASTER data,

Google Image, Census of Ratnagiri district

(2001, 2011).

Coastal slope (%)

Adjacent land use

Seas, lakes, streams

Table 2. Study area criteria and sub-parameter used for identified the coastal tourism potential and

scenic beauty.

Beach

Scenic

Value

(BSV)

Details of

Parameter /

score

Low

(1)

Moderate

(2)

High

(3)

Very High

(4)

(Francesca et al.2018)

Beach

morphology

Rocky

coast

Estuaries/

lagoons

Silt /Muddy Open /barren land/

Sandy coasts / Rocky

coast

(Li Lin and Pussella

2017;Mani Murali et

al.2013; researcher

complied)

Landscape

Features

single

Landscape

Features

2 or 3

Landscape

Features

4 To 6

Landscape

Features

More than 6 Landscape

Features

(Pralong and Reynard

2005)

Beach Sand

colour

Mud sand Black

sand

White sand White and golden sand

(researcher complied)

Beach Sunrise

and sunset view

Very

Simple

view

Simple

View

Beautiful

View

Ideal views(researcher

complied)

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Beach water

clarity

Turbid Partially

Turbid

Partially

Transparent

Transparent

(Suryawanshi and

Ranyewale 2018)

Beach

Scientific

investigate

value

(BSIV)

Size of the area >0.50 ha 0.75 ha-

0.50 ha

1 – 0.75 ha >1(Cetin and Sevik

2016; researcher

complied))

Coastal slope

(%)

>1

>0.2

and <1

>0.1

and <0.2

>0 and <0.1

(Mani Murali et al.2013)

Adjacent land

use

Forest

/Shrubs

Agriculture Marshy/

water

Built up ( Li Lin and

Pussella 2017; Cetin and

Sevik 2016)

Seas, lakes,

streams

Creeks Shores of

stream

Shores of

lake

Sea cost (Cetin and

Sevik 2016)

Figure 2. Research Method

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3.2 Selection of criteria and sub-parameters

The researcher mention in the field of geographical study of tourism potential has

assigned scores to sub-criteria on the basis of selected coast site (Figure 3).

3.2.1 Beach Scenic Value (BSV):

i) Beach morphology:

The shape of the beach depends mainly on the internal and external forces. The open barren

land and the white golden sand are the features of this beach and they are suitable for tourism.

Being a good coastline, there is a lot of scope for tourism development.

(Sources: Maharashtra Maritime Board, 2017,https://mahammb.maharashtra.gov.in)

Figure 3. Ware beach tourism potential map

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ii) Landscape Features:

If there are different types of landscapes on the beach, then the natural beauty of the place

is more enchanting. This Ware beach is no exception as there is a huge scope for the development

of the tourist spot as there is a lot of scenic beauty.

iii) Beach Sand colour:

The color of the sand on the beach is a major tourist attraction. The natural beauty of this

beach attracts tourists as it has white golden sand on the beach. Small sand dunes are formed along

the coast as the ocean waves continue to work over the coast.

iv) Beach Sunrise and sunset view:

The enchanting view of sunrise and sunset in a calm atmosphere enchants the tourists on

the beach. The great location of Ware Beach, the natural coastline, the breathtaking sunrise and

sunset views that form over the coast are the natural tourist attractions of this coastline.

v) Beach water clarity:

The scenic beauty of the coast is mainly clean air, pollution free air and blue sea water.

Tourists visit the beaches where the water is clean. Tourists never visit a coastline whose water is

polluted. Since there is no human intervention on this coast, pollution is not found on the coast, so

the sea water on the coast is very clean and its natural features attract tourists for tourism.

3.3.2 Beach scientific investigates value (BSIV):

i) Size of the area:

The natural accessibility of the coastline depends mainly on the size of the coastal area. As

the size of the Ware beach area is about 1 hectare, it is possible to provide all kinds of services to

this place and tourists. These mainly include tourist lodging, hotels, horse riding, boating, food,

etc.

ii) Coastal slope (%):

If the slope of the coast is slow, it is considered very important for tourism development.

This factor is very important to ensure that the lives of the tourists are not endangered while they

are traveling on the beach. The slope of this coastline is mostly slow and is conducive to tourism.

In short, the development of this coastline can take place in the future if proper services are

provided at this place from the point of view of tourists.

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iii) Adjacent land use:

The coastline, which is suitable for adjacent land use has more natural tourism potential.

Considering Ware Beach, most of the area is covered by natural vegetation. GIS-based technology,

ARC GIS 9.3 was used to evaluate the presence of mixed crops, including marsh / swamps,

orchards, paddy cultivation, thorn bushes, trees, social forestry, plantation, tourism land use.

iv) Sea Lake and Stream:

Coastal tourism potential depends on the natural structure of the Sea Islands or creeks and

rivers. In addition, natural vegetation, biodiversity, golden white sand, climate, etc. adds to the

natural tourist beauty. This is why tourists visit these places. All these features are found in this

coast.

3.3 Score determination to criteria and sub-parameter:

To determine the value of all the criteria and sub-criteria selected for this, used the 9 point

scale value table (Table 3) used by Thomas (1977). In determining this value, the researcher has

collected international research materials field visit and GPS survey to identify the potential of the

tourist destination. The values of all the criteria and sub-criteria selected on the basis of 1 to 9 are

clearly shown in the accompanying table. In the present study, scores for sub-criteria were assigned

based field survey and literature review related to study area. The scores were assigned to the

criteria and sub-parameter from 1 to 9. Higher score (9) indicates higher tourism potential of sub-

parameter, so the lowest value indicates (Table 4) that the tourism potential is low (1).

Table 3.Thomas L. Saaty 9 Point scale, 1977.

Intensity of

Importance

Explanation

1 Equal importance

3 Moderate importance

5 strong importance

7 Very strong important

9 Absolutely strong important

2,4,6,8

Reciprocals

Intermediate values

Values for inverse comparison

Table 4.Beach criteria and sub-parameter

Beach

Criteria

Parameter Details of beach characteristics Weight

Beach

Scenic

Value

(BSV)

Beach morphology Open/ barren land beach, rocky

coast

9

Landscape Features More than 6 Landscape Features

8

Beach Sand colour Light & Brown 7

Beach Sunrise & sunset view Ideal view 9

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Beach water clarity Transparent

8

Beach

Scientific

investigate

value

(BSIV)

Size of area 1 – 0.75 ha 7

Coastal slope (%) 1:36 1

Adjacent land use Marshy/swamp land

Mixed crop with built up, paddy

field

Mangroves , social forest, forest,

plantation

8

Seas, lakes, streams River/Pond 1

3.4 GIS and AHP method:

GIS-software and AHP OS software considers a number of criteria in the decision-making

process for various geographical issues. It is developed for solving spatial complex problems

related to a geographical study of tourism potential and its scenic beauty. The role of the physical

criterion is significant in the decision making process.However, the weights of these criteria are

not equal in tourism potential criteria and sub-parameter. Moreover, GIS, AHP OS software and

Microsoft excel has been used for the determination of the weights of the criteria and scores of the

sub-criteria. Li Lin and Pussella 2017; Mani Murali et al. 2013; Francesca et al. 2018; Pralong and

Reynard 2005; Suryawanshi and Ranyewale 2018; Cetin and Sevik 2016; all above researcher

have been using physical criteria for weight determination for different criteria. In decision making

process, all criteria are measured according to their level of importance in AHP technique (Zolekar

and Bhagat 2015; Zolekar 2018). Therefore, AHP techniques have been used for geographical

study of coastal tourism potential in the present study.

3.5 Analytical hierarchy process

Prof. Thomas L. Saaty (1970) used the AHP techniques for solving complex problems

related to group decision making based on Mathematics. In addition, various researchers have been

using to AHP methods. The AHP method is based on weights of the criteria and is related to not

relevant decision, this is a measure the inconsistency of the decision of the respondent’s .AHP

decides the weights for different parameters using pairwise comparisons matrix (PCM).Prof. Saaty

(1980) put forward for consideration a pairwise comparison matrix, on the basis of the preference

scale.

3.5.1 Weight calculation to criteria using pairwise comparison matrix (PCM):

The field survey and literature review were used for formation of judgment between two

criteria (Table 4) and the pairwise comparison matrix table was prepared (Table5). Weights were

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calculated by normalizing the PCM. The Normalized pairwise comparison matrix has been

obtained by dividing the column elements of the matrix by the sum of each column. The row

elements in the obtained matrix are summed and the total value is divided by the number of

elements in the row. The Normalized pairwise comparison matrix was calculated using Microsoft

Excel. Thus, weights were calculated for the selected criteria (Table6).The criteria were used for

the study of tourism potential in present research development. However, all selected criteria is

not suitable for tourism for site suitability (Gaikwad and Bhagat 2017, 2018).

Table 5 Pairwise comparisons matrix

coastal

slope

Seas,

lakes,

stream

s

Size of

area

Beach

Sand

colour

Beach

water

clarity

Adjacen

t land

use

Landscap

e Features

Beach

Morpholog

y

Beach

Sunrise

&

sunset

view

1.00 1.00 0.14 0.14 0.13 0.13 0.13 0.11 0.11

1.00 1.00 1.00 0.50 0.14 0.13 0.13 0.11 0.11

7.00 1.00 1.00 1.00 0.25 0.20 0.17 0.14 0.13

7.00 2.00 1.00 1.00 0.25 0.14 0.13 0.14 0.13

8.00 7.00 4.00 4.00 1.00 0.50 0.33 0.14 0.13

8.00 8.00 5.00 7.00 2.00 1.00 0.50 0.25 0.25

8.00 8.00 6.00 8.00 3.00 2.00 1.00 1.00 0.33

9.00 9.00 7.00 7.00 7.00 4.00 1.00 1.00 1.00

9.00 9.00 8.00 8.00 8.00 4.00 3.00 1.00 1.00

58.00 46.00 33.14 36.64 21.77 12.09 6.38 3.90 3.18

Table 6 Normalized pairwise comparisons matrix

coastal

slope

Seas,

lakes,

stream

s

Size of

area

Beach

Sand

colour

Beach

water

clarity

Adjacen

t land

use

Landscap

e Features

Beach

Morpholog

y

Beach

Sunrise

& sunset

view

0.02 0.02 0.00 0.00 0.01 0.01 0.02 0.03 0.03

0.02 0.02 0.03 0.01 0.01 0.01 0.02 0.03 0.03

0.12 0.02 0.03 0.03 0.01 0.02 0.03 0.04 0.04

0.12 0.04 0.03 0.03 0.01 0.01 0.02 0.04 0.04

0.14 0.15 0.12 0.11 0.05 0.04 0.05 0.04 0.04

0.14 0.17 0.15 0.19 0.09 0.08 0.08 0.06 0.08

0.14 0.17 0.18 0.22 0.14 0.17 0.16 0.26 0.10

0.16 0.20 0.21 0.19 0.32 0.33 0.16 0.26 0.31

0.16 0.20 0.24 0.22 0.37 0.33 0.47 0.26 0.31

1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00

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Calculation of vulnerability index:

Consistency Ratio

Professor Thomas has used the consistency ratio (CR) scaling method in 1977

and its priority hierarchy (AHP). Basically the consistency ratio is calculated by dividing the result

by the consistency index value (CI) and the Random Index Value (RI) as follows. The following

formula is used for this (equation 1),

CR = CI / RI.

Consistency Index (CI) and Random Index (RI):

The following equation is used to calculate the consistency index (Saaty 1977, 1983, 1990; Wind

and Saaty1980; Mani Murali et al. 2013 ) (equation 2)

CI= (λmax− n)/ (n−1)

Table 7Values of Random index (Thomas L.Saaty.1977).

N 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

R

I

0.0

0

0.0

0

0.5

8

0.9

0

1.1

2

1.2

4

1.3

2

1.1

4

1.4

5

1.4

9

1.5

1

1.4

8

1.5

6

1.5

7

1.5

9

Where

λ (Lambda ) = Principal Eigen value of the matrix.

n = number of the matrix.

RI = the random index (Table 7)

3.9 .3 Measure the evaluation of the consistency ratio:

Professor Thomas L. Saaty (1977) statement that measure the evaluation of the consistency

ratio (CR) of a value of 0.10 or less is considered relevant or accepted its means that is a significant

priority if consistency ratio (CR) of a value of > 0.10 or < 0.1 it’s not relevant or rejects or error,

its means not significant then calculating AHP sequence (Table 7) (Rocha et al.2020; Francesca et

al.2018; Mani Murali et al.2013). All these distributions are shown in the table below (Table 8)

Table 8 Measure the evaluation consistency ratio

CR ≤ 0.10 Relevant or accepted Significant

CR > 0.10 / CR ≤ 0.1 Not relevant or rejected Not significant

3.9.3 Physical vulnerability index (PVI):

The physical vulnerability index (PVI) calculating was used (Rocha et al. 2020; Francesca

et al. 2018; Mani Murali et al. 2013; Duriyapong and Nakhapakorn 2011) the following equation

(3),

PVI=W1X1+W2X2+W3X3+W4X4+W5X5+W6X6+W7X7+W8X8+W9X9+W10X10.

Here, Weight of each physical parameter and vulnerability score of each variable.

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4. Result and Discussion:

4.1Computation of consistency ratio (CR) result:

Pairwise comparison matrix and normalized pairwise comparison matrix steps has used to

calculate the consistency ratio result (Table 5 and 6). The formula CI = (λ max− n) / (n - 1) has

used for this consistency Index ((CI=0.13). The value of the random index was

calculated with using the random index value (RI=1.45) (Table 7). Thus, using the hypothetical

findings (Table 8), a consistency ratio value has calculate (CR= 0.08). The calculation of the

consistency ratio (CR) has clearly shown in the following table 9.The fact that the calculated value

(CR=0.08) of is less than the table value (0.10), it means that the coastal tourism potential of the

Ware beach and the scenic beauty of the beach is relevant for the development of coastal tourism.

Table 9. Computation of consistency ratio (CR)

Parameters Physicalvariables

λ max 10.06

n 9

CI 0.13

RI 1.45

CR 0.08

4.2Physical vulnerability index (PVI) result:

Analyzed the criteria and sub-parameter selected to assess the potential and natural beauty

of tourism through the software AHP OS to calculate the physical insecurity index. Moreover,

physical vulnerability indexes (PVI) (equation 3) were calculating the value of all criteria and sub

parameters (table 10). The classification in this table (table 10) they're reported as preferred weight

(%), rank, and sum / final effect. The rank and priority weight of beach sunrise and sunset view

(rank 1, priority weight 28.44%), beach morphology (rank 2, priority weight 23.78%) and

landscape features (rank 3, priority weight 17.11%) appear to be the highest, meaning that this

criterion is favorable for tourism development and has the highest tourism potential.Adjacent land

use (rank 4, priority weight 11.56%), beach water clarity (rank 5, priority weight 8.22%), beach

sand color (rank 6, priority weight 3.78%) and area size (rank 7, priority weight 3.78 %) Their

location and preference weight appears to be moderate. This means that this criterion clearly

indicates that tourism development is favorable, and their tourism potential is moderate. Oceans,

lakes, streams (rank 8, priority weight 2%) and coastal slopes (rank 9, priority weight 1.56%) have

their characteristics and their tourist potential is relatively lower than other criteria. Naturally,

during the development of tourism, it is necessary to provide services to tourists regarding

maritime security. The scenic beauty of this beach is also very captivating and beautiful. In short,

all the selected criteria and parameters are favorable for coastal development. If the Government

of Maharashtra develops sustainable tourism development by providing all kinds of services along

this coastline, it will provide a lot of employment to the locals, and moreover, the development of

this beach will reduce the stress on the number of tourists on Ganpatipule Beach (Table 10).

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Table 10. Weights for the criteria based on PCM

Criteria and

sub-parameter Rank

Sum/

Final

Influence

Priority

Weight

(%)

SUM*

Priority

Weight

Classification

of

Tourism

potential

1 Coastal slope 9 0.14 1.56 0.22 Low

2 Sea ,Lakes, streams 8 0.18 2.00 0.36

3 Size of the area 7 0.34 3.78 1.28

4 Beach sand colour 6 0.34 3.78 1.28

5 Beach water clarity 5 0.74 8.22 6.08

6 Adjacent land use 4 1.04 11.56 12.02

7 Landscape features 3 1.54 17.11 26.35 High

8 Beach Morphology 2 2.14 23.78 50.58

9 Beach sunrise & sunset view 1 2.56 28.44 72.82 Very high

09 100 Mean = 19.03

SD = 26.25

4.3Classification of the Tourism potential:

The accompanying table shows the weight distribution for the criteria based on PCM. The

common pair was compared, summed up all the criteria and parameters in the matrix, and then

multiplied by the sum and the preferred weight (%). Based on this, the values of average and

standard deviation were calculated. From that the low, high and very high tourism potential table

of the classification created the tourism potential table (Table10). By multiplying the sum and

priority weights of all the criteria, their average and standard deviations were

calculated. Accordingly, the findings of the table of tourism potential have clarified as follows:

4.3.1 Low Tourism potential: Coastal slope (0.22) Sea, lake, stream (0.66) Area size (1.228) Beach sand color (1.228)

Beach water clarity (6.08) and adjacent land use (12.02), all criteria indicated low tourist potential

4.3.2 High Tourism potential:

The Beach Morphology (50.58) and Landscape Features (23.35) have indicated high

tourism potential.

4.3.3 Very High Tourism potential:

The view of sunrise and sunset on the Ware beach is very attractive; it means this criterion

(72.82) is showing very high tourism potential.

5. Conclusion: In the presented research GIS and Global Mapper software, AHP OS free software and

Microsoft excel (2007) were used and find out the geographical tourism potential and its scenic

beauty in the present research. Beach morphology, landscape features, beach sand color, beach

sunrise and sunset view and beach water clarity, coastal slope, size of the area ,adjacent land use,

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sea, lakes, stream Criteria were used to evaluate Ware beach tourism potential. The coastal tourism

potential and scenic beauty were studied on the basis of the physical vulnerability Index (PVI).

After a geographical study of all the above factors, it became clear that this coastline needs to be

developed for tourism. For this, along with the natural beauty, it is necessary to provide the

necessary financial and social services to the tourist destination. It is equally important to provide

security to the tourists at the tourist spot. If all these factors are implemented, this tourist

destination will be developed in the future and this will provide a lot of financial employment to

the local citizens in this area.

Acknowledgements:

I thank all the people who helped me during this research. My research used free AHP OS

software, I am personally thankful to for that.

Conflicts declaration of authors: The authors do not show any interest conflict.

Abbreviations: Tourism potential, Analytical Hierarchy Processes (AHP), Pairwise comparison

Matrix (PCM).

Reference:

1. Cetin, M., Zeren, I., Sevik, H. et al.(2018) A study on the determination of the natural

park’s sustainable tourism potential. Environ Monit Assess 190, 167.

https://doi.org/10.1007/s10661-018-6534-5

2. De Serio, Francesca & Armenio, Elvira & Mossa, Michele & Petrillo, Antonio.

(2018)How to Define Priorities in Coastal Vulnerability Assessment. Geosciences 8(11),

415; https://doi.org/10.3390/geosciences8110415

3. Duriyapong, F., & Nakhapakorn, K. (2011). Coastal vulnerability assessment: a case

study of Samut Sakhon coastal zone. Songklanakarin Journal of Science &

Technology, 33(4).

4. Gaikwad R D, Bhagat VS (2017) Multi-criteria watershed prioritizationof Kas Basin in

Maharashtra (India): AHP and influence approaches. Hydrosp Anal 1(1):41–61

5. Gaikwad R, Bhagat V (2018) Multi-criteria prioritization for sub-watersheds in medium

river basin using AHP and influence approaches. Hydrosp Anal Gatha Cognit. https

://doi.org/10.21523 /gcj3.18020 105

6. Goepel,K.D., (2017) BPMSG’s AHP Online System (Business Performance

Management Singapore), 53357427, 1-25. https://bpmsg.com/ahp/docs/BPMSG-AHP-

OS.pdf

7. Kişi, N.(2019) A Strategic Approach to Sustainable Tourism Development Using the

A’WOT Hybrid Method: A Case Study of Zonguldak, Turkey. Sustainability , 11, 964.

https://doi.org/10.3390/su11040964

8. Lin, Li & Pussella, Pgrni. (2017) Assessment of vulnerability for coastal erosion with

GIS and AHP techniques case study: Southern coastline of Sri Lanka. Natural Resource

Modeling, 30(4), e12146. 10.1111/nrm.12146.

9. Mani Murali, R., Ankita, M., Amrita, S., & Vethamony, P. (2013) Coastal vulnerability

assessment of Puducherry coast, India, using the analytical hierarchical process.

https://doi.org/10.5194/nhess-13-3291-2013

10. Navale,S.B and Suryawanshi R.S.(2019) Morphological Analysis of Coastal Tourism

Potential in Budal Platform, Ratnagiri District (MS), India, 6(2), 689-704,

http://doi.one/10.1729/Journal.22491

Mukt Shabd Journal

Volume IX, Issue VIII, AUGUST/2020

ISSN NO : 2347-3150

Page No : 384

11. Pralong, J. P., & Reynard, E. (2005)A proposal for a classification of geomorphological

sites depending on their tourist value. Il Quaternario, 18, 313-319,

https://doi.org/10.4000/geomorphologie.350

12. Priskin, J. (2001) Assessment of natural resources for nature-based tourism:: the case of

the Central Coast Region of Western Australia. Tourism management, 22(6), 637-

648.https://doi.org/10.1016/S0261-5177(01)00039-5

13. Rocha, C.; Antunes, C.; Catita, C.(2020) Coastal Vulnerability Assessment Due to Sea

Level Rise: The Case Study of the Atlantic Coast of Mainland

Portugal. Water,12(2),360. https://doi.org/10.3390/w12020360

14. Saaty T.L. (1987) Principles of the Analytic Hierarchy Process. In: Mumpower J.L.,

Renn O., Phillips L.D., Uppuluri V.R.R. (eds) Expert Judgment and Expert Systems.

NATO ASI Series (Series F: Computer and Systems Sciences), vol 35. Springer, Berlin,

Heidelberg

15. Saaty, T. L. (1977). A scaling method for priorities in hierarchical structures. Journal of

mathematical psychology, 15(3), 234-281. https://doi.org/10.1016/0022-

2496(77)90033-5

16. Saaty, T. L. (1990). An exposition of the AHP in reply to the paper “remarks on the

analytic hierarchy process”. Management science, 36(3), 259-268.

https://doi.org/10.1287/mnsc.36.3.259

17. Saaty, T. L. (1990). How to make a decision: the analytic hierarchy process. European

journal of operational research, 48(1), 9-26. https://doi.org/10.1016/0377-

2217(90)90057-I

18. Samanta da Costa Cristiano S., Portz L.C., Anfuso G., Rockett G.C., Barboza

E.G.(2018) , Coastal scenic evaluation at Santa Catarina (Brazil): Implications for

coastal management, Ocean and Coastal Management, 160 , pp. 146-157..

https://doi.org/10.1016/j.ocecoaman.2018.04.004

19. Suryawanshi, R. S., & Ranyewale, S. K. (2018) Tourism Potential of Geomorphosites:

A Comparative Assessment of Selected Beach Sites in Malvan Tahsil, Sindhudurg Coast

of Maharashtra (India). Transactions, 40(2), 285.

20. T. L. Saaty,(1983) "Priority setting in complex problems," in IEEE Transactions on

Engineering Management, vol. EM-30, no. 3, pp. 140-155, doi:

10.1109/TEM.1983.6448606.

21. Wind, Y., & Saaty, T. L. (1980) Marketing applications of the analytic hierarchy

process. Management science, 26(7), 641-658. https://doi.org/10.1287/mnsc.26.7.641

22. Zolekar RB, Bhagat VS (2015) Multi-criteria land suitability analysis for agriculture in

hilly zone: Remote sensing and GIS approach.Comput Electron Agric 118:300–321.

23. Zolekar, R.B. (2018) Integrative approach of RS and GIS in characterization of land

suitability for agriculture: a case study of Darna catchment. Arab J Geosci 11, 780.

https://doi.org/10.1007/s12517-018-4148-4

Website:

24. https://mahammb.maharashtra.gov.in/site/upload/pdf/GIS-SMP.pdf /01/02/2020.

25. Census of India (2011) Maharashtra, District Census Handbook Ratnagiri, Series-28

Part Xii – A Village And Town Directory Directorate Of Census Operations

Maharashtra, Ministry of Home Affairs,Mumbai,

http://censusindia.gov.in/2011census/dchb/DCHB.html 4/2/2015.

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ISSN NO : 2347-3150

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